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View Code? Open in Web Editor NEWApproximating nonlinear SVM models with RBF kernel.
License: Other
Approximating nonlinear SVM models with RBF kernel.
License: Other
*** ApproxSVM *** Approximating nonlinear SVM models with RBF kernel. This project is a C++ implementation of a second-order Maclaurin series approximation of LIBSVM models using an RBF kernel. This approximation greatly increases prediction speed for models with many support vectors but in few dimensions. For mathematical details, please refer to the associated publication at: ftp://ftp.esat.kuleuven.be/pub/SISTA/claesenm/reports/14-26.pdf In this project we only provide the implementation of the approximation. For reference, a script and data to execute most of the experiments reported in the manuscript listed above using the tools in this project are available at the following location (about 30 MB in size): http://homes.esat.kuleuven.be/~claesenm/approxsvm/examples.tar.gz If you use this software, please acknowledge it in publications. ******************************************************************* COMPILATION Depending on what facilities are available on your platform, several options exist for computations. The configure script detects presence of BLAS routines on your platform and uses them if possible. If not available, a naive (slow) fallback implementation is used instead. If you have ATLAS on your system, make sure to enable it in the configure stage using --with-atlas and include the path to the ATLAS library in LDFLAGS, for example using LDFLAGS="-L/usr/local/atlas/lib". It is strongly advised to allow the use of vector instructions using the following compiler flag: "-march=native". For a typical build, issue the following commands: ./configure CXXFLAGS="-O3 -march=native" --disable-shared make sudo make install If you get errors about loading shared libraries, issue this command: sudo ldconfig ******************************************************************* USING THE TOOLS This software package contains the following tools: approx-svm: used to approximate a given LIBSVM model with RBF kernel approx-predict: used to make predictions with an approximated model approx-analyse: analyse data set and determine maximum value for gamma for which a model can be reliably approximated approx-xval: performs k-fold cross-validation using approximated models instead of exact LIBSVM models (train-approx-predict) For an overview of command line arguments, please execute either tool without arguments or with "--help". ******************************************************************* CONTACT Please report bugs or suggestions to [email protected]. The latest version of this software is freely available at: https://github.com/claesenm/approxsvm
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